Bibliographic record
Abstract
The unprecedented rise in higher-order multiple (HOM) births and the subsequent increase in parents who want to breastfeed their babies presents community health nurses (CHNs) with complex challenges. The extraordinary diversity of the triplet breastfeeding experience once all infants are settled at home is illustrated through findings from a survey of nine mothers of triplets. Parents revealed how they managed the feedings over the multiples' first year: type of feedings (breast, expressed breast milk [EBM], formula); scheduled and demand feedings; adequacy of milk supply; frequency and duration of feedings; consecutive and simultaneous feedings; nighttime with three; weaning; effects of breastfeeding on their bodies and well-being; challenges and stresses; and spousal, family, and health professional attitudes and support. A number of strategies that CHNs can utilize are suggested. These include working with individual families as well as forming partnerships with parents of multiples' support groups, multiple birth associations, interested health professionals, and the community sector. It is through these actions that the accessibility, coordination, and quality of health, multiple birth education, and social support services can be strengthened and healthy public policies implemented which address the unique and enormous demands experienced by HOMs' families.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".